Multi-Sensor Safe Path System for Autonomous Vehicles

ABSTRACT

Systems and methods for guiding autonomous vehicles by monitoring the entire planned path and sending alert messages to a vehicle management system for delays, reroute, or emergency stop to avoid collision with an obstruction. The system initiates alternative paths when the primary path is blocked and is capable of reporting a vehicle identifier and the current positions of the vehicle and any obstruction along the planned path of the autonomous vehicle.

BACKGROUND

This disclosure generally relates to systems and methods for monitoringthe movements of autonomous vehicles in warehouses and factories andtaking actions to avoid collisions. As used herein, the term “autonomousvehicles” includes both automated guided vehicles (AGVs) that follow afixed path and mobile robots which do not follow a fixed path.

Autonomous vehicles are equipped with collision detection sensors butthe range in which they operate is limited to their on-board sensor'scoverage area. This range is commonly designed to fit a uniform areaaround the vehicle and payload. Typically autonomous vehicles havesafety features such as proximity sensors to stop the vehicle based onprogrammable distance or time to a blocking object. Also, vehiclelocation is calculated in relation to the last known node locationembedded in the path. The drawback is that the vehicle can only sensecollisions within a limited range around itself and is confined to theresponse time due to lack of information. In addition, there could beunplanned events in high traffic areas in which autonomous vehicles mustco-exist with other production activities. A current solution lacksvisibility to the entire path and controls ranges that can exceed theon-board sensors specified rating. There are other issues such asnon-line-of-sight obstructions beyond doorways that the vehicle sensorscannot detect. The existing solution does not provide redundancy and inmany cases requires an operator or spotter to follow the vehicle with acontrol pendant. This option adds additional labor and createsdependency based on human judgment instead of having a carefullyorchestrated automated system.

SUMMARY

The subject matter disclosed in some detail below is directed to systemsand methods for monitoring the entire planned path of an autonomousvehicle (i.e., an AGV or a mobile robot) and sending alert messages to avehicle management system for delays, reroute, or emergency stop toavoid collision with an object or person. The system initiatesalternative paths when the primary path of the autonomous vehicle isblocked and is capable of reporting a vehicle identifier and the currentpositions of the vehicle and any obstruction (e.g., a person or anobject) along the planned path of the autonomous vehicle.

The following discussion will focus on systems and method for guidingAGVs, but many of the technical features disclosed in detail below alsohave application to guidance of mobile robots. The proposed systemintegrates a network of distributed cameras with an AGV system in whicheach AGV is already equipped with onboard sensors for use in collisionavoidance. However, the sensor system onboard a typical AGV can only“see” a limited distance along the AGV path, not the entire plannedpath, which could be several thousand feet.

The distributed cameras and an image processing server that processesthe images acquired by those cameras enable visibility along the entireplanned path in all directions, thereby significantly enhancing the AGVsituational awareness and providing information not typically availablefrom onboard sensors. In accordance with some embodiments, the system isconfigured to share object identification and human location informationand expected collision time with an AGV so that a delay, reroute, oremergency-stop procedure can be executed by the AGV. More specifically,the AGV can respond appropriately with one of three responses: emergencystop, pause or reroute depending on what object is being detected, thelocation of that object and the length of time the path blockage hasexisted. Optionally, the proposed system also provides visual alerts tofactory workers when an AGV is approaching around a blind corner.

In accordance with at least some embodiments, the AGV is notified ofpath blockage and then selects a reroute if appropriate. Currently, atypical AGV is programmed to pause indefinitely if there is a blockagein the path, but with the enhanced sensor capability disclosed herein,the AGV will able to see the route blockage before the AGV initiates itsroute and eliminate any delays by selecting an alternative route. Thisenhanced situational awareness for AGVs is the result of synergisticallyintegrating a sensor system with an AGV system. This additionalcapability gives the AGV the opportunity to eliminate delays, increaseefficiency, keep production parts undamaged, as well as create a saferwork environment for mechanics in the area. The integration and dataexchange uniquely enhances production operations.

Although various embodiments of systems and methods for guiding AGVswill be described in some detail below, the technology applicable toboth AGVs and mobile robots may be characterized by one or more of thefollowing aspects.

One aspect of the subject matter disclosed in detail below is a methodfor guiding an autonomous vehicle (i.e., an AGV or a mobile robot) toavoid an obstruction, comprising: arranging a multiplicity of cameras tosurveil an area intersected by a planned path of an autonomous vehicle;acquiring image data using the cameras while the autonomous vehicle ismoving along the planned path in the area; processing the image data todetect a presence of and determine a current position of an object inthe area; determining whether the object has a current position relativeto a position of the autonomous vehicle that violates a constraint ornot; if the object has a current position that violates the constraint,generating data representing vehicle guidance information; convertingthe data into vehicle guidance signals having a format acceptable to avehicle management system configured for controlling movement of theautonomous vehicle; receiving the vehicle guidance signals at thevehicle management system; transmitting control signals from the vehiclemanagement system to the autonomous vehicle which are a function of thereceived vehicle guidance signals; and discontinuing a current movementof the autonomous vehicle in response to receipt of the control signals.

In accordance with at least some embodiments of the method described inthe preceding paragraph, the constraint is that the object not be inclose proximity to the autonomous vehicle. For this constraint, themethod further comprises: determining a current position of theautonomous vehicle along the planned path; determining a currentseparation distance separating the object and the autonomous vehicle;and determining whether the separation distance is less than a specifiedthreshold or not. When the separation distance is less than thespecified threshold, at least some of the vehicle guidance signalsrepresent a command to initiate an emergency-stop procedure. In responseto receipt of that command, the vehicle management system transmitscontrol signals that cause the autonomous vehicle to stop.

In accordance with at least some embodiments, the constraint is that theobject not be in an obstructing position along the planned path of theautonomous vehicle. For this constraint, at least some of the vehicleguidance signals represent a command to delay or slow down theautonomous vehicle when the object is in the obstructing position. Inone proposed implementation, the method further comprises processing theimage data to detect whether the autonomous vehicle is loaded orunloaded. If the autonomous vehicle is loaded, then the command to slowdown the autonomous vehicle includes a predetermined rate designed formaximum loading of the autonomous vehicle. In another proposedimplementation, the method further comprises: determining a current timeinterval during which the object has been in the obstructing position;and determining whether the current time interval is greater than aspecified threshold or not, wherein if the current time interval exceedsthe specified threshold, then at least some of the vehicle guidancesignals represent routing data for an alternative path of the autonomousvehicle that avoids the object.

The foregoing method further comprises: processing the image data todetect a unique identifier on the autonomous vehicle; generating vehicleidentification signals representing the unique identifier having aformat acceptable to the vehicle management system; and transmitting thevehicle identification signals to the vehicle management system alongwith the vehicle guidance signals.

Another aspect of the subject matter disclosed in detail below is asystem for guiding an autonomous vehicle (i.e., an AGV or a mobilerobot), comprising: an autonomous vehicle configured to travel along aplanned path that intersects an area; a vehicle management systemconfigured for controlling movement of the autonomous vehicle; amultiplicity of cameras arranged to surveil the area; an imageprocessing server connected to receive image data acquired by themultiplicity of cameras during surveillance of the area and configuredto process the image data to detect a presence of and determine acurrent position of an object in the area; a path control serverconnected to receive processed data from the image processing server andconfigured to determine whether the object has a current positionrelative to a position of the autonomous vehicle that violates aconstraint or not, and if the object has a current position thatviolates the constraint, generate data representing vehicle guidanceinformation; and an interface configured to convert the data from thepath control server into vehicle guidance signals having a formatacceptable to the vehicle management system. The vehicle managementsystem is communicatively coupled to receive the vehicle guidancesignals from the interface and is configured to transmit control signalsfrom the vehicle management system to the autonomous vehicle which are afunction of the received vehicle guidance signals. The autonomousvehicle is communicatively coupled to receive the control signals fromthe vehicle management system and is configured to discontinue a currentmovement in response to receipt of the control signals.

In accordance with at least some embodiments of the system described inthe preceding paragraph, the image processing server is furtherconfigured to determine a current position of the autonomous vehiclealong the planned path, the constraint is that the object not be inclose proximity to the current position of the autonomous vehicle, andthe path control server is further configured to determine a currentseparation distance separating the object and the autonomous vehicle andthen determine whether the separation distance is less than a specifiedthreshold or not, wherein when the separation distance is less than thespecified threshold, at least some of the vehicle guidance signalsrepresent a command to initiate an emergency-stop procedure.

In accordance with at least some embodiments of the system, theconstraint is that the object not be in an obstructing position alongthe planned path of the autonomous vehicle, and at least some of thevehicle guidance signals represent a command to delay or slow down theautonomous vehicle when the object is in the obstructing position. Inaddition, the path control server is further configured to: determine acurrent time interval during which the object has been in theobstructing position; determine whether the current time interval isgreater than a specified threshold or not; and if the current timeinterval exceeds the specified threshold, determine an alternative pathfor the autonomous vehicle that avoids the object, wherein at least someof the vehicle guidance signals represent routing data for thealternative path.

In accordance with at least some embodiments of the system, the imageprocessing server is further configured to process the image data todetect a unique identifier on the autonomous vehicle; and the interfaceis further configured to generate vehicle identification signalsrepresenting the unique identifier having a format acceptable to thevehicle management system.

A further aspect of the subject matter disclosed in detail below is amethod for guiding an autonomous vehicle, comprising: acquiring pathdata representing a planned path to be traveled by the autonomousvehicle; arranging a multiplicity of cameras to surveil an areaintersected by the planned path of the autonomous vehicle; acquiringimage data using the cameras while the autonomous vehicle is movingalong the planned path in the area; processing the image data to detecta presence of and determine a current position of an object in the area;determining whether the object in its current position obstructs theplanned path of the autonomous vehicle or not; if the object obstructsthe planned path of the autonomous vehicle, generating data representingvehicle guidance information; converting the data into vehicle guidancesignals representing a command to alter a current movement of theautonomous vehicle having a format acceptable to a vehicle managementsystem configured for controlling movement of the autonomous vehicle;receiving the vehicle guidance signals at the vehicle management system;transmitting control signals from the vehicle management system to theautonomous vehicle which are a function of the received vehicle guidancesignals; and altering a current movement of the autonomous vehicle inresponse to receipt of the control signals.

Other aspects of systems and methods for guiding an autonomous vehicleare disclosed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The features, functions and advantages discussed in the precedingsection can be achieved independently in various embodiments or may becombined in yet other embodiments. Various embodiments will behereinafter described with reference to drawings for the purpose ofillustrating the above-described and other aspects. None of the diagramsbriefly described in this section are drawn to scale.

FIG. 1 is a diagram representing an orthographic view of a typical AGVhaving a guidance unit.

FIG. 2 is a diagram representing an orthographic view of a multiplicityof AGVs (of the type depicted in FIG. 1) moving inside a manufacturingfacility.

FIG. 3 is a diagram showing a floor plan of a generic factory withlocations of cameras and access points for wirelessly communicating withan AGV that is configured to follow a fixed path (indicated by dashedlines).

FIG. 4 is a block diagram identifying components of a system formonitoring an AGV along an entire planned path and sending alertmessages to initiate delays, reroute, or emergency stop to avoidcollision.

FIG. 5 is a block diagram identifying components of a vehicle monitoringsystem in accordance with some embodiments.

FIG. 6 is a block diagram identifying additional components of a systemfor monitoring an AGV along an entire planned path and sending alertmessages to initiate delays, reroute, or emergency stop to avoidcollision.

FIG. 7 is a flowchart identifying steps of a logic-based decision-makingprocess for determining an action to be taken to control an unloaded AGVin dependence on a status (e.g., clear or obstructed) of a planned pathof the unloaded AGV.

FIG. 8 is a flowchart identifying steps of a logic-based decision-makingprocess for determining an action to be taken to control a loaded AGV independence on a status (e.g., clear or obstructed) of a planned path ofthe loaded AGV.

FIG. 9A is a diagram showing that a time t₁ to initiate an emergencystop is selected to precede a time at which a collision will occur by aninterval of time that is greater than the interval of time needed tostop a fully loaded AGV that is moving at maximum speed.

FIG. 9B is a diagram showing that a time t₂ to initiate a delay isselected to precede the time to initiate an emergency stop depicted inFIG. 9A.

FIG. 9C is a diagram showing that a time t₃ to initiate a reroute isselected to precede the time to initiate a delay depicted in FIG. 9B.

FIG. 10 is a flowchart identifying steps of a method for rerouting anAGV in accordance with one embodiment.

FIG. 11 is a diagram representing one example of a QR code patternmarker.

Reference will hereinafter be made to the drawings in which similarelements in different drawings bear the same reference numerals.

DETAILED DESCRIPTION

Illustrative embodiments of systems and methods for guiding autonomousvehicles are described in some detail below. However, not all featuresof an actual implementation are described in this specification. Aperson skilled in the art will appreciate that in the development of anysuch actual embodiment, numerous implementation-specific decisions mustbe made to achieve the developer's specific goals, such as compliancewith system-related and business-related constraints, which will varyfrom one implementation to another. Moreover, it will be appreciatedthat such a development effort might be complex and time-consuming, butwould nevertheless be a routine undertaking for those of ordinary skillin the art having the benefit of this disclosure.

The technology disclosed herein can be used to control AGVs or mobilerobots to provide an alternative safe path or to cause the vehicle todelay or slow down when the primary path of an AGV or mobile robot isblocked by an obstacle or perform an emergency-stop procedure when aseparation distance becomes less than a specified minimum (i.e., when acollision is possible or imminent). The various embodiments disclosed insome detail hereinafter incorporate one or more of the followingfeatures:

(1) The system detects obstructions within the planned path of theautonomous vehicle and then provides primary or secondary signals to thevehicle control. The primary signals can initiate emergency stops orreroute the vehicle to a new path. The secondary signals can be used toassist the vehicle control with time and speed variables.

(2) Cooperative sensor communication makes it possible to cover anentire path and detect beyond the range of the vehicle's on-boardsensors.

(3) The system reviews the complete planned path of the autonomousvehicle in real time to initiate continuation or reroute to the vehiclemanagement system.

(4) Vehicle load and time-to-stop data is calculated in real time andcommunicated to the vehicle management system. When this data iscombined with the path status (clear or obstructed), the system canautomatically initiate signals to continue, delay, reroute, or emergencystop. Time to stop is calculated from the vehicle weight with or withoutpayload, average stopping time and maximum vehicle speed.

(5) The system has the capability to detect a unique identifier on theautonomous vehicle. This feature will identify the specific vehicle fromthe fleet and can report the status of the network of vehicles alongtheir path.

(6) The system is configured to determine the status of loaded versusempty vehicles or tugs behind the vehicle using computer vision andother sensors attached to factory walls/ceilings along the vehicle path.All sensors are networked to a central control that monitors the vehiclepath in an integrated way.

(7) The technology disclosed herein enables an external system outsideof the vehicle control to communicate with the vehicle management systemto add another layer of safety. This system will be comprised of acluster of sensors with limited field of view; however, when integratedthey are capable of tracking the same objects as they pass from onefield of view to another. The combined safe path sensors can integrateand map out the complete path with vehicles and other objects in thepath.

(8) A generic solution that is not dependent on a particular vehiclebrand, make, or model. Control systems have interfaces configured toexchange messages in a two-way format. As an example, the vehicle speedcan be communicated from the vehicle management system and utilized withload size and path status to initiate messages back to the vehiclemanagement system for suggested delay, reroute or initiation of anemergency stop procedure.

The technology disclosed in some detail below adds an extra level ofsafety by interrogating an entire vehicle travel path that may includeroll-up doors, tight corners and blind spots. In addition, the system iscapable of sending early warning signals to the vehicle operatinginfrastructure when a path is blocked by objects that could interferewith clear and safe operation. The autonomous vehicle path is notvisible to human eyes and could be easily blocked by other vehicles,pedestrians or materials. By managing the vehicle path, the system willoperate smoothly by sending out early warning signals to the vehiclemanagement system for changes in the speed or alternate routing of theautonomous vehicle whose planned path is obstructed. Data collected fromsensors will evaluate possible collisions and can initiate emergencystops to avoid accidents or property damage.

For the purpose of illustration, a system for guiding AGVs will now bedescribed in some detail. However, it should be appreciated that theconcepts, methodologies and components described with reference toproviding guidance to an AGV also have application in systems forguiding mobile robots. The prime difference between the two types ofautonomous vehicles is that the planned path of an AGV must follow oneof a multiplicity of pre-existing fixed paths, whereas the planned pathof a mobile robot is not limited to travel along pre-existing fixedpaths. More specifically, a mobile robot may travel in any directionfrom any position on a floor of a factory.

Automated guided vehicles (AGVs) may be used to perform different typesof operations. For example, these types of vehicles may be used fortowing objects, carrying loads, transporting materials, performingforklift operations, and/or performing other suitable types ofoperations. Typically, the path for an AGV is formed in or on the groundover which the AGV will move. As one illustrative example, a path may beformed by cutting a slot into the floor of a facility and embedding anelectrically conductive wire in this slot. The AGV uses a sensor todetect a radio frequency signal transmitted from the wire. The AGV usesthis detected radio frequency signal to follow the wire embedded in thefloor. In the alternative, a magnetic bar may be embedded in the slot.In another illustrative example, a path is formed by placing tape on theground. The tape may be, for example, without limitation, colored tapeor magnetic tape. An AGV may use any number of sensors to follow thepath formed by the tape. Some currently available AGVs use laser systemsand/or three-dimensional imaging systems to follow predefined paths.

FIG. 1 is a diagram representing an orthographic view of a typical AGV200 having a guidance unit 214. The AGV 200 is configured to move on theground 204 in a manufacturing facility 206. In this illustrativeexample, magnetic bar 208 is embedded in the ground 204. The AGV 200 inturn is equipped with magnetic sensors that detect the presence of themagnetic bar 208. The magnetic bar 208 defines a path on the ground 204along which the AGV 200 is to move. In this illustrative example, theAGV 200 has a guidance unit 214. The guidance unit 214 is configured tocontrol and guide movement of the AGV 200. As depicted, the guidanceunit 214 includes a sensor system 216 mounted to the AGV 200 and amotion controller 218.

For example, this sensor system 216 may comprise one or more laserscanners that scan for the presence of obstacles in the path of the AGV200. Such a laser scanner may comprise an off-the-shelf laser-baseddistance measurement device, such as a laser range meter. Measurementdata from the laser range meter can be used to obtain estimates of therespective distances from the laser range meter (i.e., from the AGV 200)to an obstacle in the AGV path. A typical laser range meter comprises alaser diode which transmits a bundled, usually visible, laser beam 210.In this example, the laser range meter may be mounted to a pan-tiltmechanism (not shown), which enables the laser range meter to be rotatedabout the pan and tilt axes. The light which is backscattered and/orreflected by the obstacle is imaged on the active surface of aphotoreceiver by receiving optics. The laser diode has a position and anorientation which are fixed relative to the position and orientation ofthe video camera; the photoreceiver has a position and an orientationwhich are fixed relative to the position and orientation of the laserdiode. The time-of-flight between transmission and reception of thelight can be used by the motion controller 218 to calculate the distancebetween the laser range meter and the obstacle.

As depicted in FIG. 1, the motion controller 218 is implemented in acontrol system 222 onboard the AGV 200. In particular, this controlsystem 222 may take the form of a computer or a processor in thisillustrative example. The motion controller 218 is configured to guidethe AGV 200 along the path defined by the magnetic bar 208. Inparticular, the motion controller 218 is configured to process the datafrom the sensor system 216. For example, in response to receiving sensordata representing an AGV-obstacle separation distance less than aspecified threshold, the motion controller 218 may issue a commandinstructing the AGV 200 to stop or slow down. The motion controller 218sends the commands to propulsion drive system 224 of the AGV 200. Inthis illustrative example, the propulsion drive system 224 is an endlesstrack system 226. The propulsion drive system 224 moves the AGV 200based on the commands received from the motion controller 218.

FIG. 2 is a diagram representing an orthographic view of a multiplicityof AGVs (of the type depicted in FIG. 1) moving in a manufacturingfacility 300. In this illustrative example, the mobile system includes afirst AGV 304, a second AGV 306, a third AGV 308 and a fourth AGV 310.The guidance system is configured to steer the different AGVs throughoutthe manufacturing facility 300. The guidance system comprises a firstguidance unit 312 configured to guide the first AGV 304, a secondguidance unit 314 configured to guide the second AGV 306, a thirdguidance unit 316 configured to guide the third AGV 308, and a fourthguidance unit 318 configured to guide the fourth AGV 310. Each of theseguidance units may be implemented in the same manner as the guidanceunit 214 depicted in FIG. 1.

The first guidance unit 312 comprises a first sensor system 322associated with the first AGV 304 and a first controller 324 implementedin a control system 326 for the first AGV 304. The second guidance unit314 comprises a second sensor system 328 associated with the second AGV306 and a second controller 330 implemented in a control system 332 forthe second AGV 306. The third guidance unit 316 comprises a third sensorsystem 334 associated with the third AGV 308 and a third controller 336implemented in a control system 338 for the third AGV 308. The fourthguidance unit 318 comprises a fourth sensor system 340 associated withthe fourth AGV 310 and a fourth controller 342 implemented in a controlsystem 344 for the fourth AGV 310. The guidance system is configured toguide the AGVs along different paths on the ground 346 of themanufacturing facility 300. The different paths are defined by aplurality 348 of magnetic bars on the ground 346. The magnetic bars 348on the ground 346 may include, for example, magnetic bars 350-353.

FIG. 3 is a diagram showing a floor plan of a generic factory having anetwork of distributed cameras 2 a-2 u mounted to either an exteriorwall 40 or one of a multiplicity of interior walls 42. However, itshould be appreciated that the cameras may instead be mounted to any oneor more of the following: ceilings, columns, walls above doors, andportable support structures placed on the floor of the factory. Theparticular locations of cameras 2 a-2 u were selected for the purpose ofillustration only. It should be appreciated that the cameras 2 a-2 mcould be placed at other locations.

Although not indicated in FIG. 3, all of the cameras 2 a-2 u areconnected to an Ethernet cable, which Ethernet cable is connected to aPower over Ethernet switch (hereinafter “camera POE switch 4” asindicated in FIG. 4). Power over Ethernet is a technology that enablesnetwork cables to carry electrical power. The cameras 2 a-2 u arePOE-enabled so that they receive power via the same network connectionused to send image data from the cameras 2 a-2 u to a processor (notshown in FIG. 3, but see path control server 6 in FIG. 4). In addition,each of cameras 2 a-2 u is a type of digital video camera commonlyreferred to as an “Internet protocol camera”, meaning that it can sendand receive data via a computer network and the Internet.

FIG. 3 also includes a dashed line representing a fixed path 30 on thefactory floor 20 along which an AGV 10 is configured to travel. In thesituation depicted in FIG. 3, the AGV 10 is initially located at one endof the fixed path 30 and can travel along the fixed path 30 to anotherend point 32 of the fixed path 30. When the AGV 10 reaches the end point32, it can travel in the opposite direction along the same fixed path30. Although in the example depicted in FIG. 3, the fixed path 30comprises a series of straight path segments which intersect at rightangles, the fixed path 30 is not limited to this geometry. For example,mutually orthogonal straight path segments could be connected byarc-shaped path segments or by straight path segments that lie along thehypotenuse of a right triangle having sides aligned with the mutuallyorthogonal straight path segments. Alternatively, the fixed path 30could consist of straight and curved path segments or curved pathsegments only.

As the AGV 10 travels along the fixed path 30, the communicationsprocessor (not shown) onboard the AGV 10 communicates wirelessly withthe closest wireless access point of a plurality of wireless accesspoints 26 (see FIG. 10) having fixed locations in the factory. In theexample depicted in FIG. 3, two wireless access points 26 a and 26 b areshown. However, any number of distributed wireless access points 26 canbe provided. Each wireless access point 26 a and 26 b can be placed onthe factory floor 20, suspended from a ceiling (not shown in FIG. 3) ormounted to an interior wall 42.

Although not shown in FIG. 3, other AGVs or objects may be present onthe factory floor 20. The technology disclosed herein is particularlyconcerned with objects inside the factory which may be currentlypositioned on the fixed path 30 while the AGV 10 is moving toward theobject. In some cases, the object will be stationary; in other cases theobject is moving along the fixed path 30 in a direction toward the AGV10 or in a direction away from the AGV 10, but at a sufficiently slowerrate than the rate of the AGV 10 that a collision may ultimately occur.As used herein, the term “obstruction” should be construed broadly toencompass any one of these cases: i.e., an object that is stationary onthe fixed path and toward which the AGV 10 is moving; or an object thatis moving along the fixed path 30 and toward which the AGV 10 is moving,the object either moving in a direction opposite to the direction ofmovement of the AGV 10 or moving in the same direction at a sufficientlyslow rate that the AGV 10 will overtake the object.

FIG. 4 is a block diagram identifying components of a system formonitoring an AGV 10 along any portion of a planned path (e.g., alongthe fixed path 30 depicted in FIG. 3) and sending alert messages to avehicle management system 8 to initiate delays, reroute, or emergencystop to avoid collision. As used herein, the term “planned path” (asapplied to AGVs only) means the portion of a fixed path that extendsfrom the current position of the AGV to the destination of the AGV(which may be the end point 32 of the fixed path 30). The vehiclemanagement system 8 is configured for controlling movement of the AGV10, including sending control signals for altering the planned path ofthe AGV 10 when an obstruction is detected.

Still referring to FIG. 4, the system for guiding an AGV 10 furthercomprises a multiplicity of cameras 2 arranged to surveil an areaintersected by the planned path of the AGV 10. To enable determinationof the coordinates of the position of an object in the frame ofreference of the factory, the position and orientation of each camera inthe frame of reference of the factory are measured precisely.Preferably, each camera 2 has a field of view equal to 180 degrees. Thecameras 2 are distributed in a way such that the system has visibilityto the entire fixed path 30. In some instances, the cameras are arrangedto create overlapping fields of view. The distributed cameras 2 arecollectively able to cover an entire facility or workspace. Preferablysome cameras 2 are located such that their fields of view are capable ofencompassing non-line-of-sight obstructions beyond doorways and aroundcorners.

The system depicted in FIG. 4 further comprises an image processingserver 12 connected to receive the image data acquired by themultiplicity of cameras 4 during surveillance of the area. The cameras 2provide partial views to the image processing server 12, which isconfigured to reconstruct the entire view and then dynamically update atwo-dimensional map. More specifically, the image processing server 12is configured to process the image data to detect a presence of anddetermine a current position of an object in the area. In accordancewith at least some embodiments, the image processing server 12 isfurther configured to determine a current position of the AGV 10 alongthe planned path and to process the image data to detect a uniqueidentifier on the AGV 10. More specifically, the image processing server12 may be configured to perform a localization function whereby thecurrent position of an object or an AGV is derived from the image data.Various methods for obtaining location information using a mapconstructed from image data acquired by cameras are known in the art.The concept employed in one such system is that object distances arecalculated by a triangular relationship from two different cameraimages. For example, two images of the same object acquired fromopposite directions can be combined into a single image usinghomography. The size and center position of the object image on thetwo-dimensional map can be calculated.

The system depicted in FIG. 4 further comprises a path control server 6connected to receive processed data from the image processing server 12and configured to determine whether the object has a current positionrelative to a position of the AGV 10 that violates a constraint or not,and if the object has a current position that violates the constraint,generate data representing vehicle guidance data. In accordance with atleast some embodiments, the constraint is that the object not be inclose proximity to the current position of the AGV 10, in which casesthe path control server 6 is further configured to determine a currentseparation distance separating the object and the AGV 10 and thendetermine whether the separation distance is less than a specifiedthreshold or not. When the separation distance is less than thespecified threshold, at least some of the vehicle guidance datarepresents a command to initiate an emergency-stop procedure. Inaccordance with at least some embodiments, the constraint is that theobject not be in an obstructing position along the planned path of theAGV 10, in which cases at least some of the vehicle guidance datarepresents a command to delay or slow down the AGV 10 when the object isin the obstructing position. In these embodiments, the path controlserver 6 is further configured to: determine a current time intervalduring which the object has been in the obstructing position; determinewhether the current time interval is greater than a specified thresholdor not; and if the current time interval exceeds the specifiedthreshold, determine an alternative path for the AGV 10 that avoids theobject, wherein at least some of the vehicle guidance data representrouting data for the alternative path.

The vehicle management system 8 is communicatively coupled to receivesignals in a specified format that contain the vehicle guidance data andis configured to transmit control signals to the AGV 10 which are afunction of that vehicle guidance data. The AGV 10 is communicativelycoupled to receive the control signals from the vehicle managementsystem 8 and is configured to discontinue or alter a current movement inresponse to receipt of the control signals.

FIG. 5 identifies some components of a vehicle monitoring system 8 inaccordance with one embodiment. The vehicle monitoring system 8 in thisembodiment includes a traffic control computer 22 (e.g., a personalcomputer) that is communicatively coupled via wired Ethernet connectionsto the path control server 6 for receiving vehicle guidance signals. Thetraffic control computer 22 is configured to output digital routinginformation which may or may not be dependent on the actionableinformation contained in the vehicle guidance data received from thepath control server 6. In addition, vehicle monitoring system 8 includesa master programmable logic controller 18 (hereinafter “master PLC 18”)that is communicatively coupled via wired Ethernet connections to thetraffic control computer 22 for receiving the routing information. Aprogrammable logic controller (a.k.a. programmable controller) is anindustrial digital computer which has been ruggedized and adapted forthe control of automated manufacturing processes. In this embodiment,the master PLC 18 is configured to output AGV control signals to an AGV10 that conforms to the routing information received from the trafficcontrol computer 22. In accordance with one implementation, the masterPLC 18 consists of a switch 24 and a communications processor 28 that iscoupled to switch 24 for two-way wired Ethernet communicationstherebetween.

The communications processor 28 is configured to receive routinginformation from the traffic control computer 22 via the switch 24,process that routing information, and then send AGV control signals tothe AGV 10 and other AGVs (not shown) via the switch 24 and one or moreaccess points 26. The switch 24 sends the AGV control signals to accesspoints 26 via wired Ethernet connections, while each access point 26broadcasts the same AGV control signals via a wireless Ethernetconnection. More specifically, each access point 26 is configured totransmit radiofrequency signals via a transmitting antenna 44 a andreceive radiofrequency signals via a receiving antenna 44 b. Similarly,each AGV 10 is configured to transmit radiofrequency signals via atransmitting antenna 46 a and receive radiofrequency signals via areceiving antenna 46 b.

The above-described technology enables an external system (i.e., thepath control server 6) outside of the vehicle control to communicatewith the vehicle management system 8 to add another layer of safety tothe layer already incorporated in the AGV system. The system disclosedherein comprises a multiplicity of cameras with limited fields of view;however, when integrated they are capable of tracking the same objectsas they pass from one field of view to another. The cameras 4 incombination provide image data that the image processing server 12 usesto integrate and map out the complete path with vehicles and otherobjects in the planned path of any autonomous vehicle.

The system is configured to provide a generic solution that is notdependent on a particular autonomous vehicle brand, make, or model.Vehicle control systems have interfaces configured to exchange messagesin a two-way format. As an example, the vehicle speed can becommunicated from the vehicle management system 8 to the path controlserver 6 and utilized with load size and path status to initiate alertmessages back to the vehicle management system 8 for suggested delay,reroute or initiation of an emergency stop procedure.

FIG. 6 is a block diagram identifying additional components (e.g.,interface 16 of a system for monitoring an AGV along an entire plannedpath and sending alert messages to initiate delays, reroute, oremergency stop to avoid collision. The system initiates alternativepaths when the primary path is blocked and is capable of reporting thevehicle position and identification number along the path. Thetechnology disclosed herein can be used to control AGVs or mobile robotsto provide an alternative safe path or to cause the vehicle to slow downwhen the primary path of an autonomous vehicle is blocked by an obstacleor when a collision is imminent.

Referring to FIG. 6, the image processing server 12 is a computer systemconfigured to receive image data from a multiplicity of distributedcameras 2 and then process that image data (including extractingactionable intelligence from the image data). More specifically, theimage processing server 12 is connected to receive image data acquiredby the multiplicity of cameras 2 during surveillance of an area which isintersected by the AGV path. In addition, the image processing server 12is configured to process the image data to detect a presence of anddetermine a current position of an object in the area. The image data isanalyzed and the results of the analysis are pushed to the path controlserver 6 for storage and further processing. The data flow out of theimage processing server 12 may also be sent to external networks toprovide other capabilities.

The path control server 6 is a computer system configured to receive theimage processing output from the image processing server 12 and thenoutput vehicle guidance data which is a function of the image processingresults using a logic tree. More specifically, the path control server 6is connected to receive processed data from the image processing server12 and configured to determine whether the object has a current positionrelative to a position of the AGV 10 that violates a constraint or not,and if the object has a current position that violates the constraint,generate data representing vehicle guidance information. The pathcontrol server 6 advises the vehicle management system 8 regarding theoverall status of the AGV path and provides detailed control actions inorder to avoid near-miss or emergency situations.

The interface 16 is the communications protocol and data that is passedfrom the path control server 6 to the vehicle management system 8. Theinterface 16 is configured to convert the data from the path controlserver 6 into vehicle guidance signals having a format acceptable to thevehicle management system 8. Different interfaces can be configured toenable the path control server 6 to communicate with vehicle managementsystems commercially available from different AGV suppliers.

The vehicle management system 8 is configured to control the AGV system.It provides operating instructions and diagnostics to any vehicles andto remote computers on the network. In accordance with the embodimentsdisclosed herein, the vehicle management system 8 is communicativelycoupled to receive the vehicle guidance signals from the interface 16and is configured to transmit control signals to the AGV 10 which are afunction of the received vehicle guidance signals. Since the vehiclemanagement system 8 is supplier-specific, the interface 16 is configuredto address this issue by receiving data in a common format and thenconverting it to the specific format required by the supplier-specificvehicle management system. The vehicle guidance signals output by theinterface 16 enter the vehicle management system 8 via an EtherCAT(Ethernet for Control Automation Technology) connection. These vehicleguidance signals include advice or commands, which the vehiclemanagement system 8 may accept or reject. More specifically, the vehicleguidance signals may include AGV path status (i.e., clear orobstructed), the identification and position of the AGV 10, the positionof an obstacle, and logic-based advice on future actions. The systemdisclosed herein has the ability to oversee an entire planned path of anautonomous vehicle. The AGV 10 is communicatively coupled to receive thecontrol signals from the vehicle management system 8 and is configuredto discontinue or alter a current movement in response to receipt of thecontrol signals.

As subsequent raw image data is received from the cameras 4, that datacan be processed by the image processing server 12 to detect an updatedposition resulting from the subsequent movement by the AGV 10. This datarepresenting current movements and paths of the AGV 10 is received bythe path control server 6, which compares the incoming data to storeddata representing the pre-programmed paths and headings. The datarepresenting the pre-programmed paths and headings (i.e., referencemovements 14 in FIG. 6) is loaded onto the path control server 6 toreference a nominal state. In order to make a logical decision, the pathcontrol server 6 is configured to refer to this database whichreferences the baseline AGV path layout and programs. The path controlserver 6 is configured to output results in dependence on observeddeviations from nominal operations and iterative camera input back intothe system.

In accordance with some embodiments, the path control server 6 isconfigured with an algorithm that can determine the precise location ofthe AGV 10 at every point during travel from one end to the other end offixed path 30. The path control server 6 is also configured with analgorithm that can determine the precise location of any obstacle 202(see FIG. 1) that may appear in the camera images. In addition, the pathcontrol server 6 is configured with an algorithm that can determine theseparation distance separating the AGV 10 and obstacle 202 at everymoment in time. The path control server 6 is further configured with analgorithm that can determine what control action to take when theestimated separation distance becomes less than a specified threshold.Typically the control action is to trigger the transmission of vehicleguidance signals to the vehicle management system 8, which vehicleguidance signals contain digital information representing a recommendedaction to be taken, for example, delay, reroute, or emergency stop theAGV 10 to avoid collision. Other algorithms may be executed for thepurpose of extracting other types of actionable information from thecamera image data. For example, pattern recognition algorithms wellknown in the art can be employed. In particular, such patternrecognition algorithms can be used to detect a visible identificationpattern applied on a surface of the AGV 10 that is within the field ofview of at least one camera 2.

FIG. 7 is a flowchart identifying steps of a logic-based decision-makingprocess 50 (also referred to herein as a “logic tree”) for determiningan action to be taken to control an unloaded AGV 52 in dependence on astatus (e.g., clear or obstructed) of a planned path of the unloaded AGV52. This logic-based decision-making process 50, which is performed bythe path control server 6, comprises the following logical decisions andactions.

First, the path control server 6 determines whether there is an objectin an obstructing position along the planned path of the unloaded AGV52. If there is an object in an obstructing position, the path controlserver 6 determines the current time interval during which the objecthas been in the obstructing position. A determination is then madewhether the current time interval is greater than or less than aspecified threshold (e.g., 3 minutes). In accordance with the logicdepicted in FIG. 7, if the current time interval t of the obstruction isless than three minutes (status 58), then the path control server 6generates vehicle guidance data representing a command to delay or slowdown the unloaded AGV 52 (action 60). This vehicle guidance data doesnot include advice concerning an alternative route. In contrast, if thecurrent time interval t of the obstruction is greater than three minutes(status 54), then the path control server 6 generates vehicle guidancedata representing a command to delay or slow down the unloaded AGV 52and further comprising routing data representing an alternative path(action 56). The path control server 6 is further configured todetermine a current separation distance d separating the object and theunloaded AGV 52 and then determine whether the separation distance d isless than a specified threshold (e.g., 2 ft) or not. If the separationdistance is less than the specified threshold (e.g., d<2 ft), i.e., theobject is in close proximity (status 62), then the path control server 6generates vehicle guidance data representing a command to initiate anemergency-stop procedure (action 64). If the AGV path is clear (status66), then the path control server 6 does not generate any vehicleguidance data representing an action to be taken or an alternative pathto be followed (action 68).

FIG. 8 is a flowchart identifying steps of a logic-based decision-makingprocess 70 (also referred to herein as a “logic tree”) for determiningan action to be taken to control a loaded AGV 72 in dependence on astatus (e.g., clear or obstructed) of a planned path of the loaded AGV72. This logic-based decision-making process 70, which is performed bythe path control server 6, comprises the following logical decisions andactions.

First, the path control server 6 determines whether there is an objectin an obstructing position along the planned path of the loaded AGV 72.If there is an object in an obstructing position, the path controlserver 6 determines the current time interval during which the objecthas been in the obstructing position. A determination is then madewhether the current time interval is greater than or less than aspecified threshold (e.g., 3 minutes). In accordance with the logicdepicted in FIG. 8, if the current time interval t of the obstruction isless than three minutes (status 78), then the path control server 6generates vehicle guidance data representing a command to delay or slowdown the loaded AGV 72 (action 80) at a predetermined rate designed formaximum loading conditions. This vehicle guidance data does not includeadvice concerning an alternative route. In contrast, if the current timeinterval t of the obstruction is greater than three minutes (status 74),then the path control server 6 generates vehicle guidance datarepresenting a command to delay or slow down the loaded AGV 72 at apredetermined rate designed for maximum loading conditions and furthercomprising routing data representing an alternative path (action 76).The path control server 6 is further configured to determine a currentseparation distance d separating the object and the loaded AGV 72 andthen determine whether the separation distance d is less than aspecified threshold (e.g., 2 ft) or not. If the separation distance isless than the specified threshold (e.g., d<2 ft), i.e., the object is inclose proximity (status 82), then the path control server 6 generatesvehicle guidance data representing a command to initiate anemergency-stop procedure (action 84). If the AGV path is clear (status86), then the path control server 6 does not generate any vehicleguidance data representing an action to be taken or an alternative pathto be followed (action 88).

A loaded AGV 72 traversing a straight path will result in differentcalculated deceleration rates than a load AGV moving along a curved pathdue to AGV programming. A typical AGV can traverse corners and curves atthe same speed as the speed at which it traverses a straight path, butto maintain accuracy, the AGV programming reduces the maximum speed ofthe vehicle.

The timing for the issuance of vehicle guidance signals will vary independence on the type of action to be taken. FIG. 9A is a diagramshowing that a time t₁ to initiate an emergency stop is selected toprecede a time at which a collision will occur by an interval of timethat is greater than the interval of time needed to stop a fully loadedAGV that is moving at maximum speed. FIG. 9B is a diagram showing that atime t₂ to initiate a delay is selected to precede the time t₁ toinitiate an emergency stop depicted in FIG. 9A. FIG. 9C is a diagramshowing that a time t₃ to initiate a reroute is selected to precede thetime t₂ to initiate a delay depicted in FIG. 9B.

FIG. 10 is a flowchart identifying steps of a method 100 for reroutingan AGV 10 in accordance with one embodiment. The path control server 6is configured to process and prioritize each order or command (step 102)and then generate routing data (step 104). That routing data is thensent to the master PLC 18 (step 106) as part of the information carriedby the vehicle guidance signals output by the interface 16. The masterPLC 18 then selects a routing table, packages it and sends the packageto an AGV 10 via an access point 26. If the AGV 10 moves from thecoverage range (cell) of one access point 26 to the coverage range(cell) of another access point 26, the wireless connection is maintained(this is called roaming). The routing data is received by the AGV 10,buffered and sent to an onboard processor for processing on a firstin/first out basis (step 110). The onboard processor processes therouting data to generate commands (step 112). The appropriate actuatorsonboard the AGV 10 then execute those commands (step 114) in a mannerthat causes the AGV 10 to follow the alternative path.

As disclosed in some detail hereinabove, the cameras 2 and imageprocessing server 12 capture the details and information needed forintegrated logic-based decision-making. Images captured by the cameras 2are entered into object and location detection algorithms (executed bythe image processing server 12), which process the image data todetermine what types of objects are in motion and in the predeterminedAGV path. A code pattern or fiducial marker imprinted on the AGV 10enables the system to image processing server 12 separate an AGV 10 fromany other object. This allows the software running on the path controlserver 6 to utilize the baseline AGV path to predict future events andadvise the AGV control software running on the traffic control computer22 (see FIG. 5) on isolated events.

A respective code pattern marker can be applied on a surface of each AGV10. The payload in each code pattern marker contains a unique identifieridentifying each AGV 10. The cameras 2 acquire images of theenvironment, including any code pattern markers within their fields ofview. The image processing server 12 is configured to read and decodethe AGV identification codes printed on the code pattern markers.

One example of a suitable commercially available code pattern is a QRcode. QR codes are a type of two-dimensional barcode (a.k.a. matrixbarcode) which have integrated registration fiducial symbols (a.k.a.registration marks). FIG. 11 is a diagram representing one example of aQR code pattern marker 34. The QR code pattern marker 34 comprises aflexible substrate 36 having a QR code pattern 35 printed thereon. TheQR code pattern 35 comprises a payload 37 consisting of data thatidentifies the AGV 10 to which the QR code pattern marker 34 is adheredto. In addition, the QR code pattern 35 comprises a registrationfiducial symbol 38 a in a lower left-hand corner of the code pattern, aregistration fiducial symbol 38 b in an upper left-hand corner of thecode pattern, and a registration fiducial symbol 38 c in an upperright-hand corner of the code pattern.

While systems and methods for guiding autonomous vehicles have beendescribed with reference to various embodiments, it will be understoodby those skilled in the art that various changes may be made andequivalents may be substituted for elements thereof without departingfrom the scope of the teachings herein. In addition, many modificationsmay be made to adapt the teachings herein to a particular situationwithout departing from the scope thereof. Therefore it is intended thatthe claims not be limited to the particular embodiments disclosedherein.

The embodiments disclosed above use one or more computer systems. Asused in the claims, the term “computer system” comprises a singleprocessing or computing device or multiple processing or computingdevices that communicate via wireline or wireless connections. Suchprocessing or computing devices typically include one or more of thefollowing: a processor, a controller, a central processing unit, amicrocontroller, a reduced instruction set computer processor, anapplication-specific integrated circuit, a programmable logic circuit, afield-programmable gated array, a digital signal processor, and/or anyother circuit or processing device capable of executing the functionsdescribed herein. The above examples are exemplary only, and thus arenot intended to limit in any way the definition and/or meaning of theterm “computer system”.

The methods described herein may be encoded as executable instructionsembodied in a non-transitory tangible computer-readable storage medium,including, without limitation, a storage device and/or a memory device.Such instructions, when executed by a processing or computing system,cause the system device to perform at least a portion of the methodsdescribed herein.

The process claims set forth hereinafter should not be construed torequire that the steps recited therein be performed in alphabeticalorder (any alphabetical ordering in the claims is used solely for thepurpose of referencing previously recited steps) or in the order inwhich they are recited unless the claim language explicitly specifies orstates conditions indicating a particular order in which some or all ofthose steps are performed. Nor should the process claims be construed toexclude any portions of two or more steps being performed concurrentlyor alternatingly unless the claim language explicitly states a conditionthat precludes such an interpretation.

1. A method for guiding an autonomous vehicle to avoid an obstruction,comprising: arranging a multiplicity of cameras to surveil an areaintersected by a planned path of an autonomous vehicle; acquiring imagedata using the cameras while the autonomous vehicle is moving along theplanned path in the area; processing the image data to detect a presenceof and determine a current position of an object in the area;determining that the current position of the object relative to aposition of the autonomous vehicle violates a constraint; generatingdata representing vehicle guidance information after determining thatthe current position of the object violates the constraint; convertingthe data into vehicle guidance signals having a format acceptable to avehicle management system configured for controlling movement of theautonomous vehicle; receiving the vehicle guidance signals at thevehicle management system; transmitting control signals from the vehiclemanagement system to the autonomous vehicle which are a function of thereceived vehicle guidance signals; and discontinuing a current movementof the autonomous vehicle in response to receipt of the control signals,wherein the constraint is at least one of the following: (a) that theobject not be in close proximity to the autonomous vehicle; and (b) thatthe object not be in an obstructing position along the planned path ofthe autonomous vehicle.
 2. The method as recited in claim 1, furthercomprising determining a current position of the autonomous vehiclealong the planned path, wherein the position of the autonomous vehiclethat is used to determine whether the constraint has been violated isthe current position.
 3. The method as recited in claim 2, wherein theconstraint is that the object not be in close proximity to theautonomous vehicle, further comprising: determining a current separationdistance separating the object and the autonomous vehicle; anddetermining whether the separation distance is less than a specifiedthreshold or not, wherein when the separation distance is less than thespecified threshold, at least some of the vehicle guidance signalsrepresent a command to initiate an emergency-stop procedure.
 4. Themethod as recited in claim 3, further comprising transmitting controlsignals from the vehicle management system that cause the autonomousvehicle to stop in response to receipt by the vehicle management systemof vehicle guidance signals representing a command to initiate anemergency-stop procedure.
 5. The method as recited in claim 1, whereinthe constraint is that the object not be in an obstructing positionalong the planned path of the autonomous vehicle, and wherein at leastsome of the vehicle guidance signals represent a command to delay orslow down the autonomous vehicle when the object is in the obstructingposition.
 6. The method as recited in claim 5, further comprisingprocessing the image data to detect whether the autonomous vehicle isloaded or unloaded, wherein if the autonomous vehicle is loaded, thenthe command to slow down the autonomous vehicle includes a predeterminedrate designed for maximum loading of the autonomous vehicle.
 7. Themethod as recited in claim 5, further comprising: determining a currenttime interval during which the object has been in the obstructingposition; and determining whether the current time interval is greaterthan a specified threshold or not, wherein if the current time intervalexceeds the specified threshold, then at least some of the vehicleguidance signals represent routing data for an alternative path of theautonomous vehicle that avoids the object.
 8. The method as recited inclaim 1, further comprising: processing the image data to detect aunique identifier on the autonomous vehicle; generating vehicleidentification signals representing the unique identifier having aformat acceptable to the vehicle management system; and transmitting thevehicle identification signals to the vehicle management system alongwith the vehicle guidance signals.
 9. The method as recited in claim 1,wherein the autonomous vehicle is an automated guided vehicle.
 10. Themethod as recited in claim 1, wherein the autonomous vehicle is a mobilerobot.
 11. A method for guiding an autonomous vehicle, comprising:acquiring path data representing a planned path to be traveled by theautonomous vehicle; arranging a multiplicity of cameras to surveil anarea intersected by the planned path of the autonomous vehicle;acquiring image data using the cameras while the autonomous vehicle ismoving along the planned path in the area; processing the image data todetect a presence of and determine a current position of an object inthe area; determining that the current position of the object obstructsthe planned path of the autonomous vehicle; generating data representingvehicle guidance information after determining that the current positionof the object obstructs the planned path of the autonomous vehicle;converting the data into vehicle guidance signals representing a commandto alter a current movement of the autonomous vehicle having a formatacceptable to a vehicle management system configured for controllingmovement of the autonomous vehicle; receiving the vehicle guidancesignals at the vehicle management system; transmitting control signalsfrom the vehicle management system to the autonomous vehicle which are afunction of the received vehicle guidance signals; and altering acurrent movement of the autonomous vehicle in response to receipt of thecontrol signals.
 12. The method as recited in claim 11, furthercomprising transmitting control signals from the vehicle managementsystem that cause the autonomous vehicle to delay or slow down inresponse to receipt by the vehicle management system of the command. 13.The method as recited in claim 11, further comprising processing theimage data to detect whether the autonomous vehicle is loaded orunloaded, wherein if the autonomous vehicle is loaded, then the commandto slow down the autonomous vehicle includes a predetermined ratedesigned for maximum loading of the autonomous vehicle.
 14. The methodas recited in claim 11, further comprising: determining a current timeinterval during which the object has obstructed the planned path of theautonomous vehicle; and determining whether the current time interval isgreater than a specified threshold or not, wherein if the current timeinterval exceeds the specified threshold, then at least some of thevehicle guidance signals represent routing data for an alternative pathof the autonomous vehicle that avoids the object.
 15. The method asrecited in claim 11, further comprising: processing the image data todetect a unique identifier on the autonomous vehicle; generating vehicleidentification signals representing the unique identifier having aformat acceptable to the vehicle management system; and transmitting thevehicle identification signals to the vehicle management system alongwith the command to alter a current movement of the autonomous vehicle.16. A system for guiding an autonomous vehicle, comprising: anautonomous vehicle configured to travel along a planned path thatintersects an area; a vehicle management system configured forcontrolling movement of the autonomous vehicle; a multiplicity ofcameras arranged to surveil the area; an image processing serverconnected to receive image data acquired by the multiplicity of camerasduring surveillance of the area and configured to process the image datato detect a presence of and determine a current position of an object inthe area; a path control server connected to receive processed data fromthe image processing server and configured to determine when the objecthas a current position relative to a position of the autonomous vehiclethat violates a constraint and then generate data representing vehicleguidance information, wherein the constraint is at least one of thefollowing: (a) that the object not be in close proximity to theautonomous vehicle; and (b) that the object not be in an obstructingposition along the planned path of the autonomous vehicle; and aninterface configured to convert the data from the path control serverinto vehicle guidance signals having a format acceptable to the vehiclemanagement system, wherein the vehicle management system iscommunicatively coupled to receive the vehicle guidance signals from theinterface and is configured to transmit control signals from the vehiclemanagement system to the autonomous vehicle which are a function of thereceived vehicle guidance signals, and wherein the autonomous vehicle iscommunicatively coupled to receive the control signals from the vehiclemanagement system and is configured to discontinue a current movement inresponse to receipt of the control signals.
 17. The system as recited inclaim 16, wherein the image processing server is further configured todetermine a current position of the autonomous vehicle along the plannedpath, the constraint is that the object not be in close proximity to thecurrent position of the autonomous vehicle, and the path control serveris further configured to determine a current separation distanceseparating the object and the autonomous vehicle and then determinewhether the separation distance is less than a specified threshold ornot, wherein when the separation distance is less than the specifiedthreshold, at least some of the vehicle guidance signals represent acommand to initiate an emergency-stop procedure.
 18. The system asrecited in claim 16, wherein the constraint is that the object not be inan obstructing position along the planned path of the autonomousvehicle, and wherein at least some of the vehicle guidance signalsrepresent a command to delay or slow down the autonomous vehicle whenthe object is in the obstructing position.
 19. The system as recited inclaim 18, wherein the path control server is further configured to:determine a current time interval during which the object has been inthe obstructing position; determine whether the current time interval isgreater than a specified threshold or not; and if the current timeinterval exceeds the specified threshold, determine an alternative pathfor the autonomous vehicle that avoids the object, wherein at least someof the vehicle guidance signals represent routing data for thealternative path.
 20. The system as recited in claim 16, wherein: theimage processing server is further configured to process the image datato detect a unique identifier on the autonomous vehicle; and theinterface is further configured to generate vehicle identificationsignals representing the unique identifier having a format acceptable tothe vehicle management system.
 21. The system as recited in claim 16,wherein the autonomous vehicle is an automated guided vehicle.
 22. Thesystem as recited in claim 16, wherein the autonomous vehicle is amobile robot.